2021, Vol. 7, No. 2 10.15678/IER.2021.0702.04
Entrepreneurial ecosystem of Luxemb
ourg: Empirical insights
into barriers and stimuli based on GEI data
Sahoum Ali Aljazzazen
A B S T R A C T
Objective: The research objective of this article is to evaluate Luxembourg’s entrepreneurship position and
performance, and compare its entrepreneurship profile with other countries, and then to investigate the main bottleneck that holds back Luxembourg’s growth in terms of entrepreneurship.
Research Design & Methods: The Global Entrepreneurship Index (GEI) approach was employed in this
re-search. This methodology focuses on institutional and individual dimensions of entrepreneurship that are linked to efficiency. Furthermore, we used a unique feature of the GEI, the Penalty for Bottleneck (PFB) meth-odology, to infer which entrepreneurial elements should be tackled and how much effort is needed to alleviate the bottleneck of the Luxembourg entrepreneurial profile.
Findings: The study results show no improvement in Luxembourg’s profile in terms of entrepreneurship from
2014 to 2016, although it has a very high GDP per capita than those with GEI higher than it. The “start-up skills” were the main bottleneck in terms of entrepreneurship performance, which lowers the overall GEI score of Lux-embourg. Therefore, the start-up skills should be improved 100% to become 0.23 in order to enhance Luxem-bourg’s GEI score by 10 points; consequently, the new overall GEI becomes 68.3.
Implications & Recommendations: To increase and develop entrepreneurship programs in Luxembourg, the
responsible authorities in Luxembourg must adapt entrepreneurship programs that target various groups of so-ciety, especially with many immigrants. It should also facilitate access to entrepreneurial and support programs to enable aspiring entrepreneurs to create their businesses. Luxembourg should also focus on refugees by strengthening the entrepreneurial programs available to them and cooperating with NGOs to overcome obsta-cles such as the language barrier.
Contribution & Value Added: This paper highlights Luxembourg’s vulnerable performance using a new approach
that combines single and institutional variables in a unique model. Additionally, what sets this research apart is the use of PFB, which is also used to uncover the components of entrepreneurship that need to be addressed.
Article type: research article
Keywords: entrepreneurship; entrepreneurial ecosystem; bottleneck’s penalty; GEI; GEM;
Luxem-bourg
JEL codes: L26, R11, F64
Received: 2 December 2020 Revised: 11 May 2021 Accepted: 13 May 2021
Suggested citation:
Aljazzazen, S.A. (2021). Entrepreneurial ecosystem of Luxemburg: Empirical insights into barriers and stimuli based on GEI data. International Entrepreneurship Review, 7(2), 43-53. https://doi.org/10.15678/ IER.2021.0702.04
INTRODUCTION
Luxembourg is a tiny country with 2500 square kilometres located between Belgium, France, and Ger-many. Immigrants make up 45.28% (248.900) of the 549.700 total populations in Luxembourg. In 2013, the number of cross-border workers was approximately 159,600 (41.1%) of the total employment in Luxembourg, where the majority of these workers came from France, Belgium, and Germany (Schinzel, 2016). Recently, Luxembourg has made several transitional measures in developing the economy to include the mining and steel industries. Moreover, Luxembourg is considered the fifth largest financial
market in Europe and the 20 largest financial markets globally. Furthermore, Luxembourg’s economic transition included attracting international companies to become the headquarters for major compa-nies, especially in the information technology field, such as Amazon, PayPal, and Google (Carr, 2018). The research objective of this article is to evaluate Luxembourg’s entrepreneurship position and performance, and compare its entrepreneurship profile with other countries, and then to investigate the main bottleneck that holds back Luxembourg's growth in terms of entrepreneurship. The Global Entrepreneurship Index (GEI) methodology is used in this paper, which examines and evaluates the nation’s overall business performance and measures the level in the country (ecosystem). This ap-proach is extraordinary because it combines quality-related institutional and individual elements that enable the performance to be calculated on an individual and institutional level in a single model (Szerb & Trumbull, 2018). The comparison of the studied country with other countries has been done through utilizing this approach. Further, with this method, the strengths and weaknesses of country perfor-mance could be distinguished and identified (Lubbadeh, 2019; Ubrežiová et al., 2008). The results show that Luxembourg has a significant hold on individual characteristics of entrepreneurship. Finally, the bottleneck methodology PFB, a unique feature of the GEI, is used to simulate a situation in which a nation can improve its performance by allocating more enterprise resources to the weakest link in the model. In order to increase its performance, the simulation implies that Luxembourg should concen-trate on start-up skills. We have thus been able to offer the country’s enterprise performance a com-prehensive, multi-level view. Besides, policy recommendations can help intensify the company’s per-formance by targeting the system’s most vulnerable link.
The rest of this paper is organized as follows: the following section reviews the literature that takes Luxembourg’s entrepreneurship into account. The section after it delves into the material and method used in this study has been explained. The following section analyses the Luxembourg entrepreneurial profile based on the GEI method, compares its profile with other countries, and makes a simulation to leverage its GEI scour relying on the FBP technique. The conclusions, limitations, implications, and rec-ommendations for future research are presented in the final section.
LITERATURE REVIEW
The prevailing belief is that entrepreneurship is the primary driver of a country’s economic develop-ment. Therefore, it reduces the unemployment rate, endorses economic growth, and boosts tech-nological innovation (Audretsch, 2012). However, the Entrepreneurship outcomes become more ac-curate and effective if it is measured and defined correctly (Ács et al., 2014). Entrepreneurship, fre-quently understood as the process of creating new enterprises (Reynolds et al., 2005) is considered an essential contribution to innovation and technological growth, driving productivity and economic growth in the end (Braunerhjelm et al., 2009). In addition, successful entrepreneurs promote knowledge transmission and create new jobs.
As recently as a decade ago, Grand-Duchy has focused on supporting start-ups, the need for diversi-fication of the economy, and the public sector’s support in Luxembourg and the private. This, in turn, affects the start-ups’ ecosystem positively and aids the entrepreneurs in initiating their own business (Gancarczyk, 2019). One of the main reasons for developing the ecosystem of entrepreneurship and in-novation in Luxembourg is the national policy on capacity building and guiding the economy towards knowledge-based industries. This committee made several recommendations include: ease of access to information, creating and facilitating channels of communication with migrants to promote initiatives, improve communication between different groups and adapt programs of initiatives and entrepreneur-ship for these groups (OECD/European Union, 2017). The percentage of immigrants in Luxembourg is relatively high, constituting 45% of the population (Schinzel, 2016). Migrants are an essential economic and socio-economic phenomenon. Migrant entrepreneurs are described as people who have come and started their own business in the immigration country. This phenomenon occurs in most developed na-tions, attracting representatives of poverty-stricken nations. Start-up is one of the forms that allow mi-grant workers to overcome barriers in the host country’s labour market (Maj & Kubiciel-Lodzińska, 2020).
Entrepreneurs face many difficulties because of the National Centre for Business Administration pol-icies in Luxembourg, which focuses on technology-based businesses. Therefore, some laws do not sup-port entrepreneurs in obtaining the necessary funding to set up their businesses. The youth self-employ-ment rate has been increased as far as a decade ago. However, the other groups remain under the E.U. self-employment average. However, the gap between genders is still exited in terms of self-employment; nevertheless, the percentage of self-employment women grew from 5.7 % in 2008 to 8.0% in 2017. Un-employment increased in Luxembourg after the global financial crisis in 2008, but it peaked at 6.7 % in 2015 and then fell to almost 5.5 % in 2017 for both genders. However, the unemployment rate remains lower than that of the EU in general, which is 7.8 % in 2017. The unemployment rate among the youth considers high relative to the other E.U. countries. The peak value was 22.6% in 2014; the following year dropped to 18.9%. However, Luxembourg’s youth unemployment rate was one and half times the un-employment rate related to the national average (OECD/European Union, 2017).
RESEARCH METHODOLOGY
The article is based on the data of the Global Entrepreneurship Monitor (GEM) for the years 2012-2016. Most of the entrepreneurial activity information used in various international comparative research in economics (macro and micro level) is provided by The Global Entrepreneurship Monitor (Głodowska, 2019). In turn, the countries level of growth can be classified based on the statistical analysis- e.g., linear regression analysis- of the provided data, for example, GDP per capita, which explains more than 60% of country entrepreneurship growth (Liñán & Fernandez-Serrano, 2014). GDP per capita plays a crucial role in boosting establishing businesses, where demand for products and opportunities is directly propor-tional to the income (Fritsch & Schroeter, 2011). Transition economies depend profoundly on the infor-mation provided by GEI at both levels, institutional and individual. Therefore, in order to succeed in tran-sition the economies and emerging new business, a set of actions required to be changed, including changes in the attitudes, abilities, and aspirations for both individuals and institutional level (Cieślik & van Stel, 2014). Entrepreneurs usually gain a sense of respect from society because of their ability to create new business, supply a new product, or develop new technology (Thornton et al., 2011).
The Global Entrepreneurship Index (GEI) has been developed as an indicator to identify and meas-ure the entrepreneurship standardization and the entrepreneurship ecosystem level in the studied country. GEI consists of three sub-indexes attitudes, abilities, and aspirations. These sub-indexes di-vided into fourteen components, called pillars (Table 1). The fourteen pillars have been identified due to their importunacy during measuring and strengthening the entrepreneurial ecosystems. These pil-lars were used to determine the quality of the entrepreneurship ecosystem or the entrepreneurial ecosystem (EE.) in a particular country through both individual and institutional variables. The data collected based on these variables is used in the sub-indexes calculation. Therefore, the overall GEI mark is calculated based on the sub-indexes scores (Ács, Szerb, Lafuente, & LIoyed, 2018).
RESULTS AND DISCUSSION
Luxembourg’s Entrepreneurial Performance Based on GEI
This section describes Luxembourg’s entrepreneurship relatively to other transition countries (Table 2), which presents overall GEI values for 95 countries, including Luxembourg. The countries sorted based on GEI value while the United States ranked first with GEI 82.5 and GDP per capita 51.884, and Burkina Faso came in the last of the list with GEI 12.5 and GDP per Capita 1.560. Countries have been divided into three divisions (group 1 consists of the lowest developed countries, group 2 consists of the medium developed countries, and group 3 consists of the highest developed countries) (Szerb & Trumbull, 2018). It is clear that Luxembourg has the second-highest GDP per capita; however, Luxem-bourg comes in rank 19 in terms of GEI score. Although it is prevalent higher GDP per capita increases start-up rates, which is one of entrepreneurship measurement factors (Pinillos & Reyes, 2011)
Table 1. The GEI Structure of the entrepreneurial ecosystem of a given economy G lo b a l E n tr e p re n e u rs h ip I n d e x
Sub-indexes Pillars Variables (ind. / inst.)
A tt it u d e s S u b -i n d e x
Opportunity Perception Opportunity Recognition Freedom
Startup Skills Skill Perception Education Risk Acceptance Risk Perception
Country Risk
Networking Know Entrepreneur
Agglomeration Cultural Support Carrier Status
Corruption A b il it ie s S u b -i n d e
x Opportunity Startup Opportunity Motivation Governance
Technology Absorption Technology Level Technology Absorption Human Capital Educational Level
Labor Market Competition Competitors Competitiveness A sp ir a ti o n S u b -i n d e x Product Innovation New Product Techtransfer Process Innovation New Technology
Science
High Growth Gazelle
Finance and Strategy Internationalization Export
Economic Complexity Risk Capital Informal Investment
Depth of Capital Market
Source: Ács et al., (2013, p. 217).
The Global Entrepreneurship Monitor (GEM) has developed the Total early-stage Entrepreneur-ial Activity (TEA) rate. TEA concerns measuring the proportion of the population that runs a new individual business (age less than three and a half years). Where the percentage of the population in Luxembourg based on the TEA rate was somewhat higher than the E.U. average, where it was 8.8%, while the average of the European Union was 6.7% during the period 2013-2017, according to reports for the period 2013-2017, the lack of available job opportunities is one of the reasons why people in Luxembourg go to entrepreneurship.
Table 3 demonstrates Luxembourg’s overall entrepreneurial profile based on institutional and in-dividual components, the fourteen pillars in general, and the three main sub-indexes (Attitudes, Abili-ties, Aspirations). We notice that Luxembourg is among the worst counties (worst 25%) in only four variables belongs to “Entrepreneurial Attitudes,” two of them in the individual variables. Namely (Risk Perception, Career Status), the rest within the institutional variables, namely education and “start-up skills,” is the only pillar within the (worst 25%). Only five variables labelled with yellow- are within the (worst 50%) and nine variables above the average (light blue). It clears that the majority of Luxembourg variables are located within the best 25% of countries.
Table 2. Luxembourg in position global entrepreneurship index rank of the country’s 2012-2016 average
Rank Country GDP GEI DEV Rank Country GDP GEI DEV
1 United States 51,884 82.5 3 49 Uruguay 19,491 34.1 2 2 Switzerland 56,395 78.9 3 50 Barbados 15,355 34.0 2 3 Canada 42,838 78.3 3 51 South Africa 12,385 33.4 2
4 Australia 43,881 74.9 3 52 Croatia 20,529 32.3 2
5 Sweden 44,576 74.7 3 53 Costa Rica 14,135 31.5 2
6 Denmark 44,709 73.7 3 54 Lebanon 13,031 31.0 2
7 United Kingdom 37,840 72.2 3 55 Kazakhstan 23,509 30.0 1
8 Ireland 52,558 70.3 3 56 Belize 7,941 29.8 2
9 Netherlands 45,951 69.2 3 57 Namibia 9,113 29.4 2
10 Finland 39,355 68.1 3 58 Macedonia 12,310 29.1 2
11 Hong Kong 54,279 67.3 3 59 Morocco 7,276 28.2 2
12 France 37,575 65.2 3 60 Thailand 15,000 27.7 2 13 Austria 44,210 65.2 3 61 Peru 11,552 27.4 2 14 Germany 43,402 64.2 3 62 Mexico 16,520 26.6 2 15 Belgium 41,216 63.3 3 63 Bulgaria 17,355 26.5 2 16 Taiwan 37,832 63.0 3 64 Panama 19,824 26.4 2 17 Israel 31,676 61.1 3 65 India 5,578 26.3 1 18 Chile 22,160 59.0 2 66 Georgia 9,008 25.3 2
19 Luxembourg 94,277 58.5 3 67 Trinidad & Tobago 31,592 25.3 2
20 Norway 63,173 58.2 3 68 Russia 24,732 24.7 2 21 Estonia 26,772 56.0 3 69 Egypt 10,079 24.2 2 22 Qatar 119,538 55.4 3 70 Philippines 6,589 23.9 1 23 Korea 33,372 53.6 3 71 Argentina 19,017 23.8 2 24 Slovenia 28,592 52.9 3 72 Iran 16,184 22.5 2 25 Singapore 78,294 52.1 3 73 Ghana 3,720 22.5 1 26 Japan 36,946 49.4 3 74 Algeria 13,207 22.2 1 27 Cyprus 31,196 48.0 3 75 Vietnam 5,386 22.2 1 28 Portugal 26,208 47.0 3 76 Nigeria 5,409 22.0 1 29 Poland 24,484 46.9 2 77 Jamaica 8,090 21.7 2 30 Lithuania 25,150 46.4 2 78 Bolivia 6,325 21.4 1 31 Spain 31,691 45.6 3 79 Indonesia 10,195 21.1 2 32 Turkey 21,871 45.0 2 80 El Salvador 7,743 20.7 2
33 Puerto Rico 33,844 44.6 3 81 Bosnia and Herzegovina 10,224 20.7 2 34 United Arab Emirates 67,133 44.6 3 82 Ecuador 10,630 20.5 2
35 Slovakia 27,489 42.8 3 83 Brazil 14,922 20.4 2
36 Latvia 22,298 42.3 2 84 Zambia 3,543 20.3 1
37 Czech Republic 28,380 40.4 3 85 Senegal 2,297 19.7 1 38 Saudi Arabia 50,458 40.2 2 86 Guatemala 7,203 18.4 2
39 Hungary 23,946 39.4 2 87 Suriname 15,371 17.9 2 40 Tunisia 10,577 38.8 2 88 Pakistan 4,367 17.5 1 41 Colombia 12,592 38.3 2 89 Libya 17.2 1 42 Italy 34,452 38.1 3 90 Malawi 1,051 16.6 1 43 Jordan 8,390 36.5 2 91 Ethiopia 1,231 15.5 1 44 China 12,765 35.9 2 92 Cameroon 740 15.3 1 45 Greece 24,092 35.9 3 93 Uganda 1,646 13.9 1 46 Malaysia 24,132 35.5 2 94 Angola 6,148 13.8 1
47 Romania 19,376 35.0 2 95 Burkina Faso 1,560 12.5 1 48 Botswana 15,271 34.3 1
Table 3. Luxembourg entrepreneurship profile at the variable level and sub-indexes (based on 2014-2016 averages)
PILLARS INSTITUTIONAL VARIABLES INDIVIDUAL VARIABLES
E n tr e p re n e u ri a l A tt it u d e s
Opportunity Perception 0.77 Freedom 0.83 Opportunity Recognition 0.68 Start-up skills 0.15 Education 0.34 Skill Perception 0.47 Risk Acceptance 0.56 Country Risk 1.00 Risk Perception 0.34 Networking 0.77 Connectivity 0.94 Know Entrepreneurs 0.54 Cultural Support 0.66 Corruption 0.91 Career Status 0.35
Entrepreneurial Attitudes 48.3 E n tr e p re n e u r-ia l A b il it ie
s Opportunity Startup 1.00 Governance 0.99 Opportunity Motivation 0.90
Technology Absorption 0.96 Technology Absorption 0.90 Technology Level 0.95 Human Capital 0.56 Labour Market 0.52 Educational Level 0.86 Competition 0.91 Competitiveness and Regulation 0.80 Competitors 1.00
Entrepreneurial Abilities 64.9 E n tr e p re n e u ri a l A sp ir a ti o n
s Product Innovation Process Innovation 1.00 Technology Transfer 0.62 Science 0.87 New Product 0.67 New Technology 0.94 0.74
High Growth 0.54 Finance and strategy 0.88 Gazelle 0.51
Internationalization 1.00 Economic complexity 0.93 Export 1.00 Risk Capital 0.90 Depth of Capital Market 0.57 Informal Investment 1.00
Entrepreneurial Aspirations 62.4
GEI 58.5 Institutional 0.80 Individual 0.73
Note: Dark blue: best 25%, Light blue: best 50%, yellow: worst 50%, Red: worst 25% Source: own elaboration based on GEI data 2012-2016 averages.
Figure 1 shows the fourteen-pillars data for Luxembourg for 2014 to 2016; we observe that the shapes of the three charts are almost identical, and the values for most of each of the fourteen pillars during this period are almost equal. Start-up skills remained the bottleneck with the lowest value equal to approximately 0.13. The value of “High growth” and “human capital” comes in second and third place with a value of less than 0.60 for high growth and approximately 0.60 for human capital. The trend of technology absorption shows a significant fall in the value from 1.00 in 2014 to 0.80 in 2015, then increased slightly in 2016. However, some pillars such as internationalization, opportunity start-up, and product innovation maintained stability within the same period with a value of almost 1.00. Moreover, there is a slight fluctuation in the value of networking and opportunity perception.
Figure 1. The time series comparison of Luxembourg’s pillar values for the period 2014-2016
Source: own elaboration based on GEI data 2012-2016 averages.
0,00 0,20 0,40 0,60 0,80 1,00 1. Opportunity… 2. Startup Skills 3. Risk Acceptance 4. Networking 5. Cultural Support 6. Opportunity… 7. Technology… 8.Human Capital 9. Competition 10. Product… 11. Process… 12. High Growth 13.… 14. Risk Capital 2014 2015 2016
Comparing Luxembourg’s Entrepreneurial Performance to Belgium and Estonia
To investigate Luxembourg’s GEI position, Figure 2 compares the value of the fourteen pillars over the years 2012-2016 for Luxembourg with one transition economy – Estonia and non-transition economy – Belgium (a neighbouring country). These two countries have been chosen for many reasons, includ-ing both countries located in the European continent; therefore, they encounter the same circum-stances that Luxembourg faced. Moreover, the Luxembourg GDP per capita greater than both coun-tries. However, Belgium’s GEI value average of 63.1 is higher than Luxembourg, while Estonia has a GEI value of 56 and is considered the highest GEI value out of the transition countries (see Table 2).
Estonia is considered one of the most prosperous countries in entrepreneurship; although it was severely affected by the global financial crisis 2008, it achieved rapid growth, which reached almost 8 %in 2011 (Szerb & Trumbull, 2018). This development was achieved through Estonia’s policy for 2014-2020, which focused on supporting high-growth start-ups and SMEs. This policy aimed to increase the Estonian economy’s growth potential by digitalizing the economy and increasing productivity. But on the other hand, Belgium focused on youth leadership through many initiatives, the most recent of which was the 2016 National Reform Program. These programs aim to sustain business and grow it beyond its initial market goals. There were also state-level initiatives in Belgium, such as the Brussels Program to Support Youth Entrepreneurship and Wallonia Support, which focused on school and uni-versity students’ entrepreneurship (OECD/EU, 2017).
Again, it is clear that “start-up skills” are the main drawback of Luxembourg entrepreneurship growth. The three countries almost had the same values of “high growth” level. The Graph shows that Belgium’s fourteen pillars almost had equal values around Belgium’s overall score, while in Lux-embourg’s case, there is a big gap between most of the fourteen pillars values to the high GDP per capita in Luxembourg.
Figure 2. The comparison of Luxembourg, Belgium, and Estonia’s pillar values
Source: own elaboration based on GEI data 2012-2016 averages.
The GEI’s analysis results contribute to improving entrepreneurship in the country of interest by clarifying the vulnerability elements in the ecosystem, reducing the differences between the compo-nents and promoting the weaker part, and so on until reaching the optimal results term of entrepre-neurship. The Penalty of Bottleneck method was developed to identify factors that lead to a decline in the overall GEI level in a particular country. Therefore, the impact of reducing the bottleneck factors will help to know the ability of this country to improve its performance (Ács et al., 2014).
0,000 0,200 0,400 0,600 0,800
1,0001. Opportunity…2. Startup Skills
3. Risk Acceptance 4. Networking 5. Cultural Support 6. Opportunity… 7. Technology… 8.Human Capital 9. Competition 10. Product… 11. Process… 12. High Growth 13.… 14. Risk Capital
A Simulation for Improving Entrepreneurship in Luxembourg
Regarding PFB (Penalty for Bottleneck) analysis, Table 4 highlights only the bottleneck feature that constrains Luxembourg’s performance. Emphasizing the previous section's mentioned section, the
Table 4. The bottleneck pillar
Pillar Required Increase in Pillar Percentage of the total new effort
Opportunity Perception 0.00 0% Start-up Skills 0.13 100% Risk Acceptance 0.00 0% Networking 0.00 0% Cultural Support 0.00 0% Opportunity Startup 0.00 0% Technology Absorption 0.00 0% Human Capital 0.00 0% Competition 0.00 0% Product Innovation 0.00 0% Process Innovation 0.00 0% High Growth 0.00 0% Internationalisation 0.00 0% Risk Capital 0.00 0%
Source: own elaboration based on GEI data 2012-2016 averages.
Table 5. The new overall GEI and pillars values based on PFB method calculation
Target GEI Change 0.10
Pillar Required Increase in Pillar Percentage of the total new effort
Opportunity Perception 0.00 0% Start-up Skills 0.23 100% Risk Acceptance 0.00 0% Networking 0.00 0% Cultural Support 0.00 0% Opportunity Startup 0.00 0% Technology Absorption 0.00 0% Human Capital 0.00 0% Competition 0.00 0% Product Innovation 0.00 0% Process Innovation 0.00 0% High Growth 0.00 0% Internationalization 0.00 0% Risk Capital 0.00 0%
Number of pillars Changed 1 should be >5 for ‘balance.’
Indices New Score Change % Of Total New Effort
ATT 0.587 0.10 100%
ACT 0.746 0.10 0%
ASP 0.715 0.09 0%
GEI 0.683 0.10 100%
Total Change 0.23
Total Change for ‘dumb’
policy 2.14
critical bottleneck in Luxembourg’s entrepreneurship advancement is the Start-up Skills. To increase Luxembourg’s overall GEI points by ten; based on The PFB method calculation Table 5, the most re-markable improvement can be achieved by alleviating the startup skills pillar 100% to become 0.23 instead of 0.13. In turn, the entrepreneurship attitude sub-indexes average becomes 58.7. Therefore, the overall GEI becomes 68.3 instead of 58.3, with an increase of 10 points. Consequently, Luxembourg ranks 10 higher than Belgium, which is located in rank 15 with GEI 63.3.
CONCLUSIONS
The main goal of this paper was to look into Luxembourg’s entrepreneurial development and make some suggestions for improving the country’s entrepreneurial results. We examined the country’s de-velopment at the institutional and individual levels using the GEI methodology. Besides, the PFB ap-proach was employed to make policy recommendations by highlighting the system’s worst-performing pillar.
We have used a novel GEI, the PFB methodology, in which Luxembourg can increase its average GEI by ten points by targeting the weakest pillars. Only one bottleneck, start-up skills in Luxem-bourg, are in the business attitudes sub-index, based on the PFB analysis. This calls for 100% of the entire effort (business policy resources) to be directed in the start-up pillar to improve Luxem-bourg’s GEI rankings by ten.
People in Luxembourg lack the skills to start a business. Studies indicate that more than three women in Luxembourg lack the skill to start a business, and this percentage is higher than the average rate in the E.U. At the same time, half of the men lack this skill, which is almost the same average in the European Union. While a third of the youth believed that they had the skills necessary to succeed in starting a new business, which is also less than the average of the E.U., according to the survey, fear constitutes an obstacle to establishing businesses for half of the population in Luxembourg, especially among young people, who reached 52.2%. To increase and develop entrepreneurship programs in Lux-embourg, the responsible authorities in Luxembourg must adapt entrepreneurship programs that tar-get various groups of society, especially with many immigrants. It should also facilitate access to en-trepreneurial and support programs to enable aspiring entrepreneurs to create their businesses. Lux-embourg should also focus on refugees by strengthening the entrepreneurial programs available to them and cooperating with NGOs to overcome obstacles such as the language barrier.
The GEI data used during the analysis are limited to the period 2012-2016. Therefore, further in-vestigation must cover a more extended or more current period than the one used in the study. The scarcity of studies on entrepreneurship in Luxembourg is also one of the limitations of this study. More-over, only Belgium and Estonia, and only at the pillar level, were comparable to the profile of Luxem-bourg. More comparison should therefore be made at all levels with different countries in Europe. GEI is also a good indicator for start-up companies to use.
In spite of its limited content, the paper helps to portray the entrepreneurial profile of Luxembourg through a unique index combining individual and institutional quality variables in one model. We con-tribute to the identification by the sub-index, pillars, and level of the variables of the weak aspect of the business profile of Luxembourg. The analysis in particular shows empirical evidence that there is a lack of population entrepreneurship as a reason for the modest performance. We have also used the PFB approach to highlight the bottlenecks in the country and offer approximate proposals on how much Luxembourg is trying to improve its bottleneck.
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Author Sahoum Ali Aljazzazen
Bachelor of Computer engineering (Yarmouk University, Jordan); Master of Business Administration (Balqa’a Applied University, Jordan); PhD Candidate in Business Administration (University of Pécs, Hungary). His re-search interests include quality management and knowledge management in the service organizations.
Correspondence to: Sahoum Ali Aljazzazen, University of Pécs, Pécs, Rákóczi út 80, 7622, Hungary, e-mail:
eng.sahoum@hotmail.com
ORCID http://orcid.org/0000-0003-1333-0802
Acknowledgementsand Financial Disclosure
The author would like to express his gratitude to Prof. László Szerb and his supervisor Dr. Roland Schmouk, which have invaluable feedback, guidance, and comments, which allowed increasing the value of this article.
Conflict of Interest
The author declares that the research was conducted in the absence of any commercial or financial relation-ships that could be construed as a potential conflict of interest.
Copyright and License
This article is published under the terms of the Creative Commons Attribution – NoDerivs (CC BY-ND 4.0) License
http://creativecommons.org/licenses/by-nd/4.0/ Published by Cracow University of Economics – Krakow, Poland
